DEVELOPING AN AETIOLOGY-BASED TAXONOMY OF HUMAN DISEASE. Duncan McHale UCB

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1 DEVELOPING AN AETIOLOGY-BASED TAXONOMY OF HUMAN DISEASE Duncan McHale UCB

2 Need for public-private collaboration Technical knowledge Disease biology Resources Change > 200 years of disease classification

3 Objectives of the full project Propose new aetiological / mechanism based taxonomy in 2 disease areas Immunoinflammatory disorders (RA and SLE) Neurodegeneration ( AD and PD) Initial clinical validation Create vision of new mechanistic approach to the classification of human disease

4 Pre-competitive nature Mechanistic classification of disease is precompetitive and will help Patients, Physicians Regulators Industry Agreed new classification will aid in driving getting the right drug to the right patient

5 Expected impact on the R&D process Increased homogeneity of disease will: Decrease trial sizes Improve benefit risk profiles of drugs Increase speed to patients Improved understanding of the disease Ensures patients can access the right treatments for them regardless of phenotypic presentation Increased confidence in target Reduce drug discovery costs by impacting attrition

6 Suggested architecture of the project Build evidence base from: STEERING COMMITTEE Literature TOPIC A TOPIC B FUTURE TOPICS Current data Shared data Develop potential new classification WP1 Governance & Communication WP2 Knowledge and Data management WP3 R&D WP1 Governance & Communication WP2 Knowledge and Data management WP3 R&D WP1 Governance & Communication WP2 Knowledge and Data management WP3 R&D Prospective validation WP4 R&D WP4 R&D WP4 R&D WP5 Prospective Clinical trial WP5 Prospective Clinical trial WP5 Prospective Clinical trial

7 Expected contributions of the applicants Disease area expertise Multidisciplinary approach Access to pilot data and samples Access to patients to test new classification system Thinking beyond current confines of today s phenotypic classification

8 Expected (in kind) contributions of EFPIA members Baseline clinical data from clinical trials Some molecular data and samples Genetics White cell mrna Pharmacology expertise from current therapies In-vivo assay expertise Informatics and biostats expertise

9 What s in it for you? A mechanistic taxonomy Optimise benefit risk of therapies (remove patietns with no chance of responding) Identifies patients likely to benefit from new therapies despite different phenotypic features Reduce overall cost of clinical development by reducing trial sizes and increasing success Improves academic research by providing more homogenous diseases to study

10 Key deliverables of the full project Proposed taxonomy for: RA SLE AD PD Topic A Topic B Initial validation Formal validation plan New diseases nominated

11 Taxonomy call 2 topics initially to form 2 separate projects The successful applicant consortia will work together where approaches are similar to create harmonisation Expect successful applicants to collaborate with other initiatives which will add value to this one e.g. etriks If successful then additional calls focussing on other disease areas will follow

12 Questions? Contact the IMI Executive Office Website:

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